\documentclass{sig-alternate}
\usepackage{graphics,graphicx}
\usepackage{subfigure}
\usepackage{multirow}
\usepackage{algorithm}
\usepackage{algorithmic}
\usepackage{url}
\usepackage{paralist}
\usepackage{amssymb}
\usepackage{epstopdf}
\usepackage{enumerate}
\usepackage{amsmath}

\usepackage{etoolbox}
\makeatletter
\patchcmd{\maketitle}{\@copyrightspace}{}{}{}
\makeatother

\DeclareGraphicsRule{.tif}{png}{.png}{`convert #1 `dirname #1`/`basename #1 .tif`.png}

% Define format new commands
\newcount\colveccount
\newcommand*\colvec[1]{
        \global\colveccount#1
        \begin{pmatrix}
        \colvecnext
}
\def\colvecnext#1{
        #1
        \global\advance\colveccount-1
        \ifnum\colveccount>0
                \\
                \expandafter\colvecnext
        \else
                \end{pmatrix}
        \fi
}
%%%%%%

\def\sharedaffiliation{%
\end{tabular}
\begin{tabular}{c}}

\begin{document}

\title{Portfolio Allocation using Black-Litterman Model}

\numberofauthors{4}
    \author{
      \alignauthor Congxing Cai \\
      \texttt{congxing@gmail.com}\\
%
     \alignauthor Raoul Clements \\
     \texttt{raoul.clements@gmail.com}\\
%
\and
%
      \alignauthor  Dominique Gilbert\\
      \texttt{dominique.a.gilbert@gmail.com}\\
%
      \alignauthor Ahmad Salman \\
      \texttt{salman.aas@gmail.com}\\
%
      \sharedaffiliation
      \affaddr{STATS240P Final Project, Fall 2012} \\
      \affaddr{Stanford Center for Professional Development}
    }
\maketitle

\begin{abstract}
This project\footnote{The project has a website with all the source code and documentations: \url{http://code.google.com/p/bl-240-car} } studies the effectiveness of the Black-Litterman model for 6 Fama-French portfolios with varying company size and book-to-market ratios. Multiple predictive models, such as AR and AR(1)-GARCH(1,1), were developed for each Fama-French portfolio to generate future predictions for the Black-Litterman model. Market volatility, measured by the CBOE VIX index, was incorporated in an attempt to improve portfolio returns. The Black-Litterman models were then compared to Markowitz M-V portfolio optimization model based on the cumulative returns and Sharpe ratio over a 20 year period. In an attempt to quantify the implications of transaction costs that were not considered in the Black-Litterman and Markowitz M-V portfolio optimization models, a measure to estimate the degree of investment capital redistribution through time was provided. However, the VIX expanding window models delivers the highest cumulative returns and Sharpe ratio out of all tested models. 
\end{abstract}

\section{Introduction}
\label{sec:intro}
\input{intro}

\section{Equilibrium Risk Prima}
\label{sec:prima}
\input{prima}

\section{Investor View Vector}
\label{sec:view}

\subsection{ARMA Models}
\label{sec:arma}
\input{arma}

\subsection{AR-GARCH Models}
\label{sec:garch}
\input{garch}

\subsection{VIX Models}
\label{sec:vix}
\input{vix}

\section{Black-Litterman Portfolios}
\label{sec:bl}
\input{bl}

\section{Evaluation}
\label{sec:eval}
\input{eval}

\section{Turnover Rate}
\label{sec:turnover}
\input{turnover}

\bibliographystyle{abbrv}
\scriptsize
\bibliography{report}

\end{document}  